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Identification of Biomarkers for Early Diagnosis of Acute Myocardial Infarction

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Zeitschriftentitel: Journal of Cellular Biochemistry
Personen und Körperschaften: Ge, Wen‐Han, Lin, Yong, Li, Sen, Zong, Xuefeng, Ge, Zhong‐Chun
In: Journal of Cellular Biochemistry, 119, 2018, 1, S. 650-658
Format: E-Article
Sprache: Englisch
veröffentlicht:
Wiley
Schlagwörter:
Cell Biology
Molecular Biology
Biochemistry
author_facet Ge, Wen‐Han
Lin, Yong
Li, Sen
Zong, Xuefeng
Ge, Zhong‐Chun
Ge, Wen‐Han
Lin, Yong
Li, Sen
Zong, Xuefeng
Ge, Zhong‐Chun
author Ge, Wen‐Han
Lin, Yong
Li, Sen
Zong, Xuefeng
Ge, Zhong‐Chun
spellingShingle Ge, Wen‐Han
Lin, Yong
Li, Sen
Zong, Xuefeng
Ge, Zhong‐Chun
Journal of Cellular Biochemistry
Identification of Biomarkers for Early Diagnosis of Acute Myocardial Infarction
Cell Biology
Molecular Biology
Biochemistry
author_sort ge, wen‐han
spelling Ge, Wen‐Han Lin, Yong Li, Sen Zong, Xuefeng Ge, Zhong‐Chun 0730-2312 1097-4644 Wiley Cell Biology Molecular Biology Biochemistry http://dx.doi.org/10.1002/jcb.26226 <jats:title>ABSTRACT</jats:title><jats:sec><jats:label /><jats:p>Acute myocardial infarction (AMI) is a common disease with serious consequences in mortality and cost. Here we aim to screen the differentially expressed genes (DEGs) as biomarkers for early diagnosis of AMI. The microarray data of AMI was downloaded from Gene Expression Omnibus (GEO), including two independent types of research GSE66360 and GSE62646. The DEGs between control and processed samples were screened out by using limma package. Meanwhile, we performed functional analysis of GO terms and/or KEGG pathways to observe the enriched pathways of the DEGs. Finally, regression analysis of raw data was performed by using packet affyPLM in R language. Dataset GSE62646 contained 53 DEGs (FC log2&gt;1 and <jats:italic>P</jats:italic> value &lt;0.05) between first‐day samples from 28 STEMI patients and control samples from 14 patients without myocardial infarction history. There were 12 up‐regulated and 41 down‐regulated genes, 35 DEGs annotated. In GSE66360, a total of 3034 DEGs between 32 AMI patients and 38 healthy persons were obtained, including 1861 up‐regulated and 1173 down‐regulated DEGs. The comparison of the DEGs in two datasets revealed four common up‐regulated genes (EGR1, STAB1, SOCS3, TMEM176A). In enrichment analysis, STAB1, SOCS3, EGR1 involved in metabolic regulation and signaling pathways related to coronary artery disease with a characteristic change (<jats:italic>P</jats:italic> &lt; 0.05). The DEGs, especially the four up‐regulated common genes, could serve as biomarkers for early diagnosis of AMI. Additionally, the relative biological pathways these DEGs enriched in might provide a good reference to explore the molecular expression mechanism of AMI. J. Cell. Biochem. 119: 650–658, 2018. © 2017 Wiley Periodicals, Inc.</jats:p></jats:sec> Identification of Biomarkers for Early Diagnosis of Acute Myocardial Infarction Journal of Cellular Biochemistry
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title Identification of Biomarkers for Early Diagnosis of Acute Myocardial Infarction
title_unstemmed Identification of Biomarkers for Early Diagnosis of Acute Myocardial Infarction
title_full Identification of Biomarkers for Early Diagnosis of Acute Myocardial Infarction
title_fullStr Identification of Biomarkers for Early Diagnosis of Acute Myocardial Infarction
title_full_unstemmed Identification of Biomarkers for Early Diagnosis of Acute Myocardial Infarction
title_short Identification of Biomarkers for Early Diagnosis of Acute Myocardial Infarction
title_sort identification of biomarkers for early diagnosis of acute myocardial infarction
topic Cell Biology
Molecular Biology
Biochemistry
url http://dx.doi.org/10.1002/jcb.26226
publishDate 2018
physical 650-658
description <jats:title>ABSTRACT</jats:title><jats:sec><jats:label /><jats:p>Acute myocardial infarction (AMI) is a common disease with serious consequences in mortality and cost. Here we aim to screen the differentially expressed genes (DEGs) as biomarkers for early diagnosis of AMI. The microarray data of AMI was downloaded from Gene Expression Omnibus (GEO), including two independent types of research GSE66360 and GSE62646. The DEGs between control and processed samples were screened out by using limma package. Meanwhile, we performed functional analysis of GO terms and/or KEGG pathways to observe the enriched pathways of the DEGs. Finally, regression analysis of raw data was performed by using packet affyPLM in R language. Dataset GSE62646 contained 53 DEGs (FC log2&gt;1 and <jats:italic>P</jats:italic> value &lt;0.05) between first‐day samples from 28 STEMI patients and control samples from 14 patients without myocardial infarction history. There were 12 up‐regulated and 41 down‐regulated genes, 35 DEGs annotated. In GSE66360, a total of 3034 DEGs between 32 AMI patients and 38 healthy persons were obtained, including 1861 up‐regulated and 1173 down‐regulated DEGs. The comparison of the DEGs in two datasets revealed four common up‐regulated genes (EGR1, STAB1, SOCS3, TMEM176A). In enrichment analysis, STAB1, SOCS3, EGR1 involved in metabolic regulation and signaling pathways related to coronary artery disease with a characteristic change (<jats:italic>P</jats:italic> &lt; 0.05). The DEGs, especially the four up‐regulated common genes, could serve as biomarkers for early diagnosis of AMI. Additionally, the relative biological pathways these DEGs enriched in might provide a good reference to explore the molecular expression mechanism of AMI. J. Cell. Biochem. 119: 650–658, 2018. © 2017 Wiley Periodicals, Inc.</jats:p></jats:sec>
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author Ge, Wen‐Han, Lin, Yong, Li, Sen, Zong, Xuefeng, Ge, Zhong‐Chun
author_facet Ge, Wen‐Han, Lin, Yong, Li, Sen, Zong, Xuefeng, Ge, Zhong‐Chun, Ge, Wen‐Han, Lin, Yong, Li, Sen, Zong, Xuefeng, Ge, Zhong‐Chun
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container_issue 1
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description <jats:title>ABSTRACT</jats:title><jats:sec><jats:label /><jats:p>Acute myocardial infarction (AMI) is a common disease with serious consequences in mortality and cost. Here we aim to screen the differentially expressed genes (DEGs) as biomarkers for early diagnosis of AMI. The microarray data of AMI was downloaded from Gene Expression Omnibus (GEO), including two independent types of research GSE66360 and GSE62646. The DEGs between control and processed samples were screened out by using limma package. Meanwhile, we performed functional analysis of GO terms and/or KEGG pathways to observe the enriched pathways of the DEGs. Finally, regression analysis of raw data was performed by using packet affyPLM in R language. Dataset GSE62646 contained 53 DEGs (FC log2&gt;1 and <jats:italic>P</jats:italic> value &lt;0.05) between first‐day samples from 28 STEMI patients and control samples from 14 patients without myocardial infarction history. There were 12 up‐regulated and 41 down‐regulated genes, 35 DEGs annotated. In GSE66360, a total of 3034 DEGs between 32 AMI patients and 38 healthy persons were obtained, including 1861 up‐regulated and 1173 down‐regulated DEGs. The comparison of the DEGs in two datasets revealed four common up‐regulated genes (EGR1, STAB1, SOCS3, TMEM176A). In enrichment analysis, STAB1, SOCS3, EGR1 involved in metabolic regulation and signaling pathways related to coronary artery disease with a characteristic change (<jats:italic>P</jats:italic> &lt; 0.05). The DEGs, especially the four up‐regulated common genes, could serve as biomarkers for early diagnosis of AMI. Additionally, the relative biological pathways these DEGs enriched in might provide a good reference to explore the molecular expression mechanism of AMI. J. Cell. Biochem. 119: 650–658, 2018. © 2017 Wiley Periodicals, Inc.</jats:p></jats:sec>
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spelling Ge, Wen‐Han Lin, Yong Li, Sen Zong, Xuefeng Ge, Zhong‐Chun 0730-2312 1097-4644 Wiley Cell Biology Molecular Biology Biochemistry http://dx.doi.org/10.1002/jcb.26226 <jats:title>ABSTRACT</jats:title><jats:sec><jats:label /><jats:p>Acute myocardial infarction (AMI) is a common disease with serious consequences in mortality and cost. Here we aim to screen the differentially expressed genes (DEGs) as biomarkers for early diagnosis of AMI. The microarray data of AMI was downloaded from Gene Expression Omnibus (GEO), including two independent types of research GSE66360 and GSE62646. The DEGs between control and processed samples were screened out by using limma package. Meanwhile, we performed functional analysis of GO terms and/or KEGG pathways to observe the enriched pathways of the DEGs. Finally, regression analysis of raw data was performed by using packet affyPLM in R language. Dataset GSE62646 contained 53 DEGs (FC log2&gt;1 and <jats:italic>P</jats:italic> value &lt;0.05) between first‐day samples from 28 STEMI patients and control samples from 14 patients without myocardial infarction history. There were 12 up‐regulated and 41 down‐regulated genes, 35 DEGs annotated. In GSE66360, a total of 3034 DEGs between 32 AMI patients and 38 healthy persons were obtained, including 1861 up‐regulated and 1173 down‐regulated DEGs. The comparison of the DEGs in two datasets revealed four common up‐regulated genes (EGR1, STAB1, SOCS3, TMEM176A). In enrichment analysis, STAB1, SOCS3, EGR1 involved in metabolic regulation and signaling pathways related to coronary artery disease with a characteristic change (<jats:italic>P</jats:italic> &lt; 0.05). The DEGs, especially the four up‐regulated common genes, could serve as biomarkers for early diagnosis of AMI. Additionally, the relative biological pathways these DEGs enriched in might provide a good reference to explore the molecular expression mechanism of AMI. J. Cell. Biochem. 119: 650–658, 2018. © 2017 Wiley Periodicals, Inc.</jats:p></jats:sec> Identification of Biomarkers for Early Diagnosis of Acute Myocardial Infarction Journal of Cellular Biochemistry
spellingShingle Ge, Wen‐Han, Lin, Yong, Li, Sen, Zong, Xuefeng, Ge, Zhong‐Chun, Journal of Cellular Biochemistry, Identification of Biomarkers for Early Diagnosis of Acute Myocardial Infarction, Cell Biology, Molecular Biology, Biochemistry
title Identification of Biomarkers for Early Diagnosis of Acute Myocardial Infarction
title_full Identification of Biomarkers for Early Diagnosis of Acute Myocardial Infarction
title_fullStr Identification of Biomarkers for Early Diagnosis of Acute Myocardial Infarction
title_full_unstemmed Identification of Biomarkers for Early Diagnosis of Acute Myocardial Infarction
title_short Identification of Biomarkers for Early Diagnosis of Acute Myocardial Infarction
title_sort identification of biomarkers for early diagnosis of acute myocardial infarction
title_unstemmed Identification of Biomarkers for Early Diagnosis of Acute Myocardial Infarction
topic Cell Biology, Molecular Biology, Biochemistry
url http://dx.doi.org/10.1002/jcb.26226